New practice helps enterprises move AI agents from pilot to production by modernizing the architecture, infrastructure and DevOps foundations they run on

AHMEDABAD, India, June 16, 2026 /PRNewswire/ -- Junkies Coder, an Ahmedabad-based software engineering company, today announced the launch of its Agentic AI & Enterprise Modernization practice, a dedicated unit built to help enterprises deploy AI agents reliably by first modernizing the legacy systems, cloud infrastructure, and delivery pipelines those agents depend on.

The launch addresses a growing gap between AI ambition and real-world execution. While enterprises are rapidly investing in AI, adoption remains challenging.

Gartner reports that fewer than 5% of enterprise applications included task-specific AI agents in 2025, a number expected to rise to 40% by the end of 2026.

However, Gartner also predicts that more than 40% of agentic AI projects will be abandoned by 2027 due to rising costs, unclear business value, and the complexity of integrating AI agents into existing legacy environments.

Supporting this, McKinsey finds that organizations with fragmented or outdated systems are 30% more likely to face AI implementation delays.

“Every enterprise board wants AI agents in production. The reason most stall isn’t the model, it’s the decade of technical debt underneath it,” said Shalehin Modasia, Managing Director of Junkies Coder.

“You cannot scale autonomous agents on brittle architecture. Our practice strengthens the foundation architecture, infrastructure, and DevOps so AI delivers measurable outcomes instead of becoming another abandoned pilot,” he added.

What the practice covers

The Agentic AI & Enterprise Modernization practice brings 4 traditionally siloed disciplines under one delivery model:

Agentic AI engineering - Designing, building, and governing task-specific and multi-agent systems with the observability and guardrails enterprises require.

Enterprise architecture & application modernization - Re-architecting legacy applications to remove the technical debt that blocks AI adoption.

Cloud infrastructure - Building scalable, cost-efficient foundations engineered for AI and agentic workloads.

DevOps & platform engineering - Establishing the CI/CD pipelines, automation, and governance that let teams ship faster and operate safely at scale.

By combining these capabilities under one accountable team, pairing enterprise application modernization services with production-grade agent delivery, Junkies Coder compresses the path from AI experiment to production while addressing the cost, value, and risk failures.

“Modernization and AI are usually sold as separate projects, and that is exactly why both underdeliver,” said Abhishek Singh, CEO of IndiaAI Mission.

“We treat them as one engineering problem, so clients see working outcomes in weeks rather than after a multi-year transformation,” he added. 

The practice arrives as Indian enterprises and global firms accelerate investment in AI-led engineering, positioning Ahmedabad as a growing hub for talent.

“This is a company press release that is not part of editorial content. No journalist of The Hindu was involved in the publication of this release.”